Role overview

Scale AI is seeking a Frontier Agents Engineer to work directly with enterprise customers deploying production AI systems. You’ll architect, integrate, and operate AI agents within complex business environments, combining software engineering, distributed systems expertise, and frontier AI technologies to transform models into reliable enterprise software.

Key responsibilities

Architect and deploy production AI systems that integrate with enterprise cloud platforms, data warehouses, internal APIs, and business applications while meeting security and compliance requirements.
Design scalable agent architectures that combine large language models, retrieval systems, memory management, tool integration, and enterprise data into reliable production workflows.
Build robust integrations allowing AI agents to safely interact with customer systems while maintaining enterprise governance standards.
Develop production infrastructure including agent runtimes, orchestration frameworks, context pipelines, and execution services that enable reliable enterprise AI deployment.
Engineer systems for reliability, observability, latency optimization, scalability, error handling, and graceful degradation in mission-critical workflows.
Deploy evaluation harnesses using benchmarks, experiments, golden datasets, and regression testing to detect quality issues before customer impact.
Partner directly with enterprise customers to understand their technical infrastructure and translate business problems into scalable AI architectures.
Serve as technical advisor for strategic accounts, leading architecture discussions and documenting reusable patterns across deployments.

Requirements

At least 4 years of software engineering experience with demonstrated expertise in distributed systems, data structures, algorithms, and system design.
Strong Python programming skills with proven experience building production software systems.
Experience building or deploying AI-powered applications using modern large language model APIs, agent frameworks, model context protocol, and retrieval systems.

What makes this role worth considering

You’ll work across the complete lifecycle of production AI systems—from architecture through deployment, operationalization, and continuous improvement. Rather than supporting a single product, you’ll solve diverse engineering challenges across industries and use cases, rapidly building expertise in enterprise architecture and AI systems engineering while working with the latest frontier AI models and methodologies as they emerge.